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Showing posts with label statistics. Show all posts
Showing posts with label statistics. Show all posts
Thursday, August 5, 2021

One Hot Encoding and Dummy Variables Generation upon a dataframe | Scenario - Perform One-Hot Encoding upon Un-Ordered Data in a sample dataframe and generate One-hot encoded feature variables | Conceptual Infographic Note

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Handling Categorical Data in Dataframe and Dataset | Types of Categorical Data and its examples | Conceptual Infographic Note

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Label Encoding and Ordinal Encoding in Python | Scenario - Perform Ordinal Encoding upon Ordered Data in a sample dataframe and generate encoded features of the data | Conceptual Infographic Note

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Sunday, July 18, 2021

An Introduction to Classification Algorithms with 10 fundamental questions | An Infographic Note with questions and answers

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  Questions Covered : Q1) What are Naive bayes Classifiers ? Q2) What do you mean by Probabilistic Classification ? Q3) What do you mean by ...
Wednesday, July 14, 2021

Infographic Note on Z-Score in Statistics and Machine Learning with it's usage scenario , calculation , implication and applications

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Sunday, June 27, 2021

Infographic Conceptual Note on Law of Large Numbers in Statistics and Machine Learning - Short Summary for Interview Questions

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Sunday, June 6, 2021

Infographic Short Note on P-value in Statistics and its applications in Machine Learning

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Saturday, June 5, 2021

Infographic Short Note on Mcnemar Test over Sample Data Space in Statistics

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Friday, May 28, 2021

Infographic Revision Short Note on Two - Way ANOVA's in Statistics , Analytics and Machine Learning

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Infographic Revision Short Note on Data Collection using Interviews in Statistics , Analytics and Machine Learning

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Infographic Revision Short Note on Statistical Data Collection using Interviews in Statistics , Analytics and Machine Learning - part 2

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Thursday, May 6, 2021

Commutative property on Matrices is not applicable

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Notes on Logistic Regression for Classification - with usage for Email Spam Recognition , Online transaction , detection of cancerous tumour , prediction of threshold values .. note part 2

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Notes on Logistic Regression for Classification - with usage for Email Spam Recognition , Online transaction , detection of cancerous tumour , prediction of threshold values

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Basic Codes on Octave for Statistical Calculations on Matrices , Vectors

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Notes on Matrices , Properties of Matrices , Inverse Matrix and Transpose of a Matrix , Regression , Scenarios on Regression , Representation of Hypothesis Equation , Gradient Descent , Cost Function

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Tuesday, May 4, 2021

Notes on - Linear Regression with one Variable with Cost Function of sample data points with difference between a Hypothesis function and Cost Function

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Monday, May 3, 2021

Definition of Machine Learning - pictorial handnotes

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Friday, April 30, 2021

Validation of Machine Learning Algorithms and Scenarios - A short article

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                                Validation of Machine Learning Codes   *   It is a widely accepted fact that just having some examples i...
Wednesday, April 28, 2021

Exploring Cost Functions in ML

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  *   The driving force behind the concept of optimization in machine learning is the response from a function which is internal to the al...